Using linear algebra for protein structural comparison and classification.

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

Bibliographic Details

Main Authors:	GOMIDE, J., MELO-MINARDI, R., SANTOS, M. A. dos, NESHICH, G., MEIRA JUNIOR, W., LOPES, J. C., SANTORO, M.
Other Authors:	JANAÍNA GOMIDE, UFMG; RAQUEL MELO-MINARDI, UFMG; MARCOS AUGUSTO DOS SANTOS, UFMG; GORAN NESHICH, CNPTIA; WAGNER MEIRA JUNIOR, UFMG; JÚLIO CÉSAR LOPES, UFMG; MARCELO SANTORO, UFMG.
Format:	Artigo de periódico biblioteca
Language:	English eng
Published:	2010-04-15
Subjects:	Protein classification, Contact maps, Linear algebra, Singular value decomposition, Latent semantic indexing, Biologia molecular, Molecular biology,
Online Access:	http://www.alice.cnptia.embrapa.br/alice/handle/doc/664383 http://dx.doi.org/10.1590/S1415-47572009000300032
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